Evidence map›Paper›PMID 34202107›Full record

ArticleVaccines2021

Modeling the Impact of COVID-19 Vaccination in Lebanon: A Call to Speed-Up Vaccine Roll Out.

Ghina R Mumtaz, Fadi El-Jardali, Mathilda Jabbour, Aya Harb, Laith J Abu-Raddad, Monia Makhoul

Abstract read
In one paragraph

Article in Vaccines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ghina R MumtazDepartment of Epidemiology and Population Health, Faculty of Health Sciences, American University of Beirut, Beirut 1107 2020, Lebanon.ORCID 0000-0003-4332-4702
Fadi El-JardaliDepartment of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut 1107 2020, Lebanon.
Mathilda JabbourDepartment of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut 1107 2020, Lebanon.
Aya HarbDepartment of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut 1107 2020, Lebanon.
Laith J Abu-RaddadInfectious Disease Epidemiology Group, Weill Cornell Medical College-Qatar, Cornell University, Qatar Foundation-Education City, Doha 24144, Qatar.ORCID 0000-0003-0790-0506
Monia MakhoulInfectious Disease Epidemiology Group, Weill Cornell Medical College-Qatar, Cornell University, Qatar Foundation-Education City, Doha 24144, Qatar.ORCID 0000-0002-0138-5286

Funding

Global Challenges Research Fund ES/P010873/1Qatar National Research Fund 12S-0216-190094Qatar National Research Fund 9-040-3-008
6 · The paper itself

Abstract

Four months into the SARS-CoV-2 vaccination campaign, only 10.7% of the Lebanese population have received at least one dose, raising serious concerns over the speed of vaccine roll-out and its impact in the event of a future surge. Using mathematical modeling, we assessed the short-term impact of various vaccine roll-out scenarios on SARS-CoV-2 epidemic course in Lebanon. At current population immunity levels, estimated by the model at 40% on 15 April 2021, a large epidemic wave is predicted if all social distancing restrictions are gradually eased and variants of concern are introduced. Reaching 80% vaccine coverage by the end of 2021 will flatten the epidemic curve and will result in a 37% and 34% decrease in the peak daily numbers of severe/critical disease cases and deaths, respectively; while reaching intermediate coverage of 40% will result in only a 10-11% decrease in each. Reaching 80% vaccine coverage by August would prevent twice as many severe/critical disease cases and deaths than if it were reached by December. Easing restrictions over a longer duration resulted in more favorable vaccination impact. In conclusion, for vaccination to have impact in the short-term, scale-up has to be rapid and reach high coverage (at least 70%), while sustaining social distancing measures during roll-out. At current vaccination pace, this is unlikely to be achieved. Concerted efforts need to be made to overcome local challenges and substantially scale up vaccination to avoid a surge that the country, with its multiple crises and limited health-care capacity, is largely unprepared for.

Indexed as

coronavirusCOVID-19epidemiologyLebanonmathematical modelSARS-CoV-2vaccine

Identifiers

PMID34202107
PMCPMC8310257

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.